def set_base_name(self, set_dir, base_job_name):
if set_dir is not None:
self.setting_dir = set_dir
else:
self.setting_dir = os.path.join(platform_id.setting_dir(),
"job_scripts")
self.base_job_name = base_job_name
self.base_name = os.path.join(self.setting_dir, self.base_job_name)
def remove_O2(vaspRundictList, nb_sites=1, redundancy=None):
""" for each structure given in argument,
remove the most oxidized oxygen
and create a VASP input folder in the job folder
option for redundancy to generate a larger supercell"""
if redundancy is None:
if input("redundancy ? Y/N")[0] == "Y":
redundancy = True
else:
redundancy = False
folder_list = []
for run in vaspRundictList:
parent_path = os.path.join(run.job_folder, "O_deficient")
print("removing O from {}".format(run.str_id))
for O_index in labile_O_indices(run, nb_sites):
print("removed O index : {}".format(O_index))
job = launch.Job.from_rundict(run)
job.structure.remove_sites([O_index])
job.entry_id = "{}_rem_O{}".format(job.entry_id, O_index)
folder_list.append(
job.set_job_folder(parent_path, explicit_jobpath=False))
job.write_data_input()
if redundancy:
job = launch.Job.from_rundict(run)
job.structure.make_supercell([1, 2, 1])
job.entry_id = "{}_big".format(job.entry_id)
folder_list.append(
job.set_job_folder(parent_path, explicit_jobpath=False))
job.write_data_input()
for folder in folder_list:
setting_dir = platform_id.setting_dir()
job_file_name = os.path.join(setting_dir, "job_scripts",
"vasp_job_double")
name = "degaz_{}".format(abs(hash(folder)))
job_string = 'sbatch -J {} --workdir {} {}'.format(
name, folder, job_file_name)
if input("LAUNCH the following [Y/n] :\n{}\n".format(
job_string)) == "Y":
subprocess.call([job_string], shell=True)
return folder_list
# from pymatgen.io.vasp.outputs import Oszicar # Outcar
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
import rw_utils.platform_id as platform_id
import structure_analysis.structure_geometry_utils as cluster
import electronic_analysis.read_mag_props as nupdown
global PARAM
# DICT of parameters to set to true or false.
PARAM = {}
PARAM['logFile'] = True # wether to print a log file of the results
PARAM['mainFolder'] = platform_id.setting_dir()
PARAM['verbose'] = 0
# DATA COLLECTION FUNCTIONS
# =========================================
def get_job_list(init_dir, file_system_choice=None):
print("\n {} \n ".format(init_dir))
if file_system_choice is None:
file_system_choice = input(
"[j]ob / [p]roject / [s]uper_project ? : ")
if file_system_choice[0] == "p":
# file_system = "p"
subdir_list = [
NELM = 100
NSW = 0
b – Lancer un calcul non – colinéaire avec VASP
/home/sol/Vasp/Vasp5/vasp.5.3.5-openmpi-nc/vasp
b1 – kill the job
c- if IBZKPT generated :
Fichier IBZKPT est écrit
(SI le Fichier KPOINT n’a pas déja la forme voulue !!)
Cp IBZPKT KPOINTS
Le fichier IBZKPTS doit contenir les points K, et la dernière colonne,
correspondant à la multiplicité des points K doit être égale a 1.
"""
settingDir = platform_id.setting_dir()
def generate_IBZKPT(folder):
shutil.copy2('INCAR', 'OLD_INCAR')
incar = Incar.from_file("INCAR")
os.remove("INCAR")
print("old incar \n", incar)
incar["ISPIN"] = 1 # spin less calculation
incar.pop("MAGMOM", None) # we don't need that anymore !
incar["ISMEAR"] = 0 # No smearing
incar["LSORBIT"] = "TRUE" # Non colinear calculation
incar["NSW"] = 0 # single point
incar["ISYM"] = 0 # no symmetry for kpts
import electronic_analysis.read_dos as DOS
import electronic_analysis.read_hull as hull
import electronic_analysis.read_mag_props as nupdown
import electronic_analysis.readO2 as O2
import electronic_analysis.rundict_utils as read
import structure_analysis.bailar_twist as bailar
import filtering_runs.filter_runs as filter_runs
import rw_utils.generic_plot as generic_plot
import rw_utils.platform_id as platform_id
print(matplotlib.get_backend())
print(sys.version)
SETTING_DIR = platform_id.setting_dir()
def filter_loop(run_list_all, input_graph_type=None, allow_filtering=True):
"""
outer loop to select (and change) the dataset
before entering the plot loop (with a fixed dataset)
"""
continue_filter_loop = True
while continue_filter_loop:
x_coord = filter_runs.select_x_coord()
if allow_filtering:
restricted_runs = filter_runs.restrict_run_list(
run_list_all, x_coord)